Skip to main content

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 358))

Abstract

We will in this paper highlight our experience with NMPC. In our context NMPC shall mean the use of a nonlinear mechanistic model, state estimation, and the solution of an online constrained nonlinear optimisation problem. Our reference base is a number of applications of NMPC in a variety of processes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. K. S. Andersen, M. Hillestad and T. Koskelainen, Model Predictive Control of a BORSTAR Polyethylene Process, In: 1st European Conference on the Reaction Engineering of Polyoleftns (ECOREP), France, 2000.

    Google Scholar 

  2. T. Drengstig, D. Ljungquist and B. A. Foss, “On the AlF 3 and Temperature Control of an Aluminum Electrolysis Cell,” IEEE Trans, of Control System Technology, vol. 6, no. 2, pp. 157–171, 1998.

    Article  Google Scholar 

  3. W. Dresler, “Limitations to carburization of high carbon ferromanganese”, In: Proceedings 1989 Steelmaking conference, 1989.

    Google Scholar 

  4. B. A. Foss, B. Lohmann and W. Marquardt, “A field study of the industrial modeling process,” Journal of Process Control, vol. 8, no. 5–6, pp. 325–338, 1997.

    Google Scholar 

  5. K. Grjotheim and H. Kvande, eds., “Introduction to aluminium electrolysis”. Aluminum-Verlag, 1993.

    Google Scholar 

  6. W. C. Li and L. T. Biegler, “Multistep, Newton-type control strategies for con-strained nonliner processes”, Chem. Eng. Res. Des., vol. 67, pp. 562–577, 1989.

    Google Scholar 

  7. N. M. C. de Oliveria and L. T. Biegler, “Constraint handling and stability prop-erties of model-predictive control,” AIChE Journal, vol. 40, pp. 1138–1155, 1994.

    Article  Google Scholar 

  8. N. M. C. de Oliveria and L. T. Biegler, “A finite-difference method for linearization in nonlinear estimation algorithms”, Automatica, vol. 31, pp. 281–286, 1995.

    Article  Google Scholar 

  9. S. J. Qin and T. A. Badgwell, “An Overview of Nonlinear Model Predictive Control”, In: Nonlinear Model Predictive Control, F. Allgower and A. Zheng Birkhauser, eds., 2000.

    Google Scholar 

  10. C. V. Rao and J. B. Rawlings, “Nonlinear Moving Horizon Estimation”, In: Non-linear Model Predictive Control, F. Allgower and A. Zheng Birkhauser, eds., 2000.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Foss, B.A., Schei, T.S. (2007). Putting Nonlinear Model Predictive Control into Use. In: Findeisen, R., Allgöwer, F., Biegler, L.T. (eds) Assessment and Future Directions of Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72699-9_33

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-72699-9_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72698-2

  • Online ISBN: 978-3-540-72699-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics